Laboratory of intelligent systems of control and forecasting2019-09-25T10:27:19+06:00

Laboratory of intelligent systems of control and forecasting

Head of the laboratory
Dr.Eng.Sc., associate professor
G.A. Samigulina

The project “Development of cognitive Smart-technology for intelligent control systems of complex objects based on artificial intelligence approaches” (2018-2020).

The objectives of the project are:

1. Conducting research in the field of bioinformatics for the development of Smart – technologies of creating systems for predicting and controlling complex dynamic nonlinear objects with various types of parameter uncertainties based on various bio-researched approaches of artificial intelligence and, in particular, the development of a promising direction of artificial immune systems.

2. Development of Smart technologies based on the creation of new modified algorithms for artificial immune systems and practical applications using them for technical, technological and social and economic complex control objects in industrial automation systems, technological processes in the oil and gas industry, education and pharmacology.

Since the leading role in the economy of Kazakhstan is assigned to the oil and gas industry and due to the growing requirements for modern industrial enterprises, as well as the rapid development of new information technologies, the development and implementation of effective intelligent control systems and diagnostics of industrial equipment in this industry is relevant.

Project Objectives:  

– Development of an effective Smart-technology for constructing dynamic intelligent control systems for complex objects based on the cognitive approach and the latest AI developments (artificial immune systems, swarm intelligence algorithms, neural networks, genetic algorithms, fuzzy set theory and multi-agent systems) for various applications.

– Synthesis of multifunctional artificial immune system consists of subsystems that implement the basic mechanisms and algorithms of functioning of the human immune system (molecular recognition, clonal selection and negative selection) for assessment and prediction of the behavior of intelligent systems, diagnostics equipment, support decision making and operational adjustment of system behavior.

– Creation of new modified IIS algorithms with the use of swarm intelligence algorithms, neural and genetic algorithms, as well as the development of software for their implementation in multifunctional IIS.

– Development of a diagnostic system for industrial equipment based on the proposed modified IIS algorithms, AMDEC approaches (Analyse Des Modes de Défaillance set des leurs Effect set leur criticité, analysis of operating modes and failures, their impact and degree of criticality) and modern microprocessor technology.

– Creation of mnemonic diagrams to control complex objects using the latest achievements in the field of artificial intelligence and cognitive technologies.

– Implementation of a multifunctional IIS based on a multi-agent approach using cognitive agents in the synthesis of intelligent control systems for various applications in industrial automation systems, technological processes in the oil and gas industry and education.

3. Creation of innovative intelligent information technologies of distance learning (with the possibility of remote access to modern existing industrial equipment of various manufacturers in the laboratories of collective use) using various non-traditional bio-tested approaches: artificial immune systems; neural networks, genetic algorithms, swarm intelligence algorithms, etc.

The problem of training professional engineers to work with modern technologies and complex industrial equipment is solved.

During the implementation of the project for 2018, the following main re-sults were obtained:

– Smart-technology for constructing intelligent control systems for complex objects based on the cognitive approach and the latest artificial intelligence developments has been developed.

– An analytical review of the current state of Artificial Immune Systems (AIS) has been carried out.

– Theoretical foundations have been developed for creating a multifunctional Artificial Immune System.

– The main control mechanisms  based on distributed control systems for Honeywell DCS are considered, as well as the principles of transmission and storage of data for use with predicted events using  the AIS approach.

– An architecture of an intelligent system based on a modified IIS (clonal selection) algorithm for integration with Honeywell DCS has been proposed.

– A multifunctional AIS has been developed based on modified swarm intelligence algorithms, cognitive technologies and a multi-agent approach.

– A modified particle swarm algorithm with inertia weight (IWPSO) has been developed for the multifunctional AIS.

– A modified cooperative particle swarm algorithm (CPSO) has been developed for the multifunctional AIS.

– The results of modeling modified particle swarm algorithms (IWPSO and CPSO) based on real production data of the Tengiz Chevroil oil and gas company for the diagnostics of industrial equipment (using daily measurements from the sensors of the U300 installation) based on the AIS have been obtained.

– A comparative analysis of the simulation results of the modified particle swarm algorithms (IWPSO and CPSO) with the classical particle swarm algorithm (PSO) has been carried out.

– An innovative cognitive smart technology based on AIS has been developed for distance learning people with visual impairments in engineering specialties in the Honeywell collective-use laboratory for training industrial equipment using the Experion PKS distributed control system. The use of cognitive approach allows to provide high-quality personalized distance learning depending on the type of Central nervous system of students (choleric, melancholic, etc.), psychophysiological features of perception and assimilation of current information, as well as features of vision taking into account the psychotype. In the future, the proposed cognitive Smart technology can be used in the development of mnemonic diagrams for managing complex technical, technological processes and providing information support for human activities, taking into account individual psychophysiological features of perception and awareness of current information.

– A unique immune network technology has been developed for constructing intelligent systems of predicting and managing complex objects under uncertainty of parameters based on the biological approach of artificial immune systems (AIS). This technology for processing and forecasting multidimensional data is aimed at reducing generalization errors and increasing the reliability of the forecast based on the properties of homologous proteins.

The research results are applied in the development of the following applications: intellectualization of industrial automation systems, diagnostics of industrial equipment, with a computer-aided molecular design of drugs with desired properties, distance learning of the engineering specialties of people with visual impairments.

The project “Development of a hardware-medical complex of assessing the psychophysiological parameters of a person” (2018-2020).

Scientific supervisor: Mazakov Talgat Zhakupovich, Dr. Sc. (Phys.-Math.),Prof.

The aim of the project is to develop new methods and technical means of assessing the psychophysiological parameters of a person.

The fundamental objective of the project is the development and research of methods and means of assessing the psychophysiological parameters of a person.

To solve this problem, the following main sub-goals are set:

  1. Automation of psychological tests in Russian.
  2. Automation of psychological tests in the Kazakh language.
  3. Development of mathematical algorithms for processing biomedical signals.
  4. Development of hardware and software evaluation. psychophysiological parameters of a person.
  5. Development of assessment of psychophysiological parameters of the person.

Scientific novelty lies in the study of existing, as well as in the development of new mathematical models and algorithms to solve the problem of developing criteria for psycho-physiological identification of a person based on interval mathematics. Practical significance consists in the development of methods and software and hardware for obtaining a psychophysiological portrait of a person, which can be applied by government and law enforcement agencies.

  1. Samigulina G.A., Samigulina Z.I. Development of Smart technology for Complex Objects prediction and Control on the Basis of a Distributed Control System and an Artificial Immune Systems Approach // Advances in Sciences, Technology and Engineering Systems Journal. – 2019. – Vol. 4, No. 3. – P.75-87. (Scopus)
  2. Samigulina G.A., Samigulina Z.I. Development of Smart-technology for Complex Objects Control based on Approach of Artificial Immune Systems // Materials of Global Smart Industry Conference (GloSIC). – Russia, 2018. – DOI:10.1109/glosic.2018.8570142. (Clarivate Analytics)
  3. Samigulina G.A., Massimkanova Zh.A. Development of Smart-technology for Forecasting Technical State of Equipment based on Modified Particle Swarm Algorithms and Immune-Network Modeling // Abstracts of The International Conference on Computational and Experimental Engineering and Sciences. – Tokyo, 2019. – P. 68-69. (Scopus)
  4. Samigulina G.A., Samigulina Z.I. Modified immune network algorithm based on the Random Forest approach for the complex objects control // Artificial Intelligence Review. – Springer, 2018. – P. 1-17. (Clarivate Analytics)
  5. Samigulina G.А., Massimkanova Zh.A. Multi-agent System for Forecasting Based on Modified Algorithms of Swarm Intelligence and Immune Network Modeling // Proceedings of the 12th International Conference Agents and Multi-agent Systems: Technologies and Applications (KES-AMSTA-18). – Australia: Springer, 2018. – P. 199-208. (Scopus)
  6. Samigulina G.A., Samigulina Z.I. Development of multi-agent technology for prediction of the «structure-property» dependence of drugs on the basis of modified algorithms of artificial immune systems // Proceedings of International Work Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2018. –Spain, Granada, April 25-27, 2018. – P. 1-2. (Clarivate Analytics)
  7. Samigulina G.А., Massimkanova Zh.A. Construction of optimal immune network model based on swarm intelligence algorithms for computer design of new drugs // Proceedings of VII International Conference «Optimization problems and their applications, OPTA-2018». – Omsk, 8-14, July 2018. – P.349-358. (Scopus)
  8. Samigulina G.A., Shayakhmetova A.S., Nyusupov A.T. Innovative intelligent technology of distance learning for visually impaired people // Open engineering. – De Gruyter, 2017. – Vol. 7, Issue 1. – P. 444-452. (Scopus)
  9. Samigulina G.A., Nyusupov A.T., Shayakhmetova A.S. Analytical review of software for multi-agent systems and their applications // Известия НАН РК. Серия геологические и технические науки. – Алматы, 2018. – № 3 (429). – C. 173-181. (Scopus)
  10. Samigulina G., Nyussupov A., Shayakhmetova A. Multi-agent Smart-system of distance learning for people with vision disabilities // of the IVth Intern.KES conf. Smart Education and e-Learning (SEEL-17). – Portugal: Springer, 2017. – P.154-166. (Thomson Reuters).
  11. Samigulina G.A., Samigulina Z.I. Intellectualization of the Data Processing in the Industrial Automatization on the basis of modern equipment // Lecture Notes in Networks and Systems. – Springer, 2017. – Р.125-137. (Scopus)
  12. Samigulina G.A., Samigulina Z.I. Immune network Technology on the Basis of Random Forest Algorithm for Computer-Aided Drug Design // Proc. 5th Int. Conference Bioinformatics and Biomedical Engineering, IWBBIO 2017. – Springer, 2017. – Vol. 10208. – P. 50-61. (Thomson Reuters)
  13. Samigulina G.A., Shayakhmetova A.S. Smart-system of distance learning of visually impaired people based on approaches of artificial intelligence // J. Open Engineering, 2016. – № 6. – Р. 359- 366 (Thomson Reuters, Scopus)
  14. Samigulina G.A., Samigulina Z.I. Intellectualization of the Data Processing in the Industrial Automatization // Proc. of the SAI Intelligent Systems Conference. – London, UK, 2016. – P. 91-101. (Scopus, Thomson Reuters)
  15. Samigulina G.A., Shayakhmetova A.S. Development of the Smart – system of distance learning visually impaired people on the basis of the combined OWL model // Proc. of the Intern. forum Smart Education and e-Learning (SEEL-16). – Spain, Tenerife, 2016. – P. 109-118. (Scopus)
  16. Samigulina G.A., Samigulina Z.I. Intelligent System of Distance Education of Engineers, based on Modern innovative Technologies // Proc. of the II Intern. Conf. on Higher Education Advances, HEAd’16. J. Social and Behavioral Sciences. – Valencia, Spain. Elsevier, 2016. – № 228. – P. 229-236. (Thomson Reuters)
  17. Samigulina G.A., Samigulina Z.I. Drag Design of sulfanilamide based on Immune Network Modeling and Ontological approach // Proceedings of the 10th IEEE International Conferences on Application of Information and Communication Technologies AICT2016. – Azerbaijan, Baku, 2016 // aict.info/2016. (Scopus)
  18. Samigulina Z.I., Shiryayeva O.I., Samigulina G.A., Fourati H. Adaptive Control strategy based reference model for Spacecraft Motion Trajectory // International Journal of Adaptive Control and Signal Processing. – Wiley, 2015. – № 29. – P. 639-652. (Thomson Reuters)
  19. Samigulina Galina, Shayakhmetova Assem. The information system of distance learning for people with impaired vision on the basis of artificial intelligence approaches // Proc. of the II Intern.conf. on Smart Education and E-learning. Smart Innovation, Systems and Technologies. – Italy, Sorrento, 2015. – Vol. 41. – P. 255-263. (Thomson Reuters)
  20. Самигулина Г.А., Самигулина З.И. Интеллектуальное компонентно – ориентированное программное обеспечение для оценки производственных рисков // Актуальные проблемы экономики. – Киев, 2015. – №6(168). – C.457-464. (Scopus)
  21. Самигулина Г.А., Шаяхметова А.С. Построение интеллектуальной системы дистанционного обучения для людей с ограниченными возможностями зрения // Матер. IV Междунар. научн. конгресса «Наука и образование в современном мире». – Новая Зеландия: Окленд, 2015. – С.848-851. (Scopus)
  22. Samigulina Galina, Samigulina Zarina. Industrial implementation of the immune network modeling of complex objects on the equipment Schneider Electric and Siemens // Proc. of Intern. Workshop on Artificial Immune Systems- Systems & Synthetic Immunology, Computational Immunology &Immune-Inspired Engineering. – Taormina, Italy, 2015. – Р. 72-81. (Scopus)
  23. Samigulina G.A., Samigulina Z.I., Wuizik W., Krak Yu. Prediction of «structure – property» Dependence of New Organic Compounds on the basis of Artificial Immune Systems // Journal of Automation and Information Sciences. – USA: Begell hause, 2015. – Vol. 47, Issue 4. – P. 28-35. (Thomson Reuters)
  24. Samigulina G.A., Samigulina Z.I. Computational Molecular Design of Antiseptic Drags based on Immune Network Modeling // Proceedings of the 12-th International Conference on Electronics Computer and Computation «ICECCO 2015». – Almaty: Suleyman Demirel University, 2015. – P. 47-51. (Scopus)
  25. Самигулина Г.А., Самигулина З.И., Вуйцих В., Крак Ю.В. Прогнозирование зависимости «структура – свойство» новых органических соединений на основе искусственных иммунных систем // Проблемы управления и информатики. – Киев, 2015. – №2. – С. 81-88. (Scopus)
  • Самигулина Г.А. Предварительная обработка данных AIS (программа для ЭВМ). Свидетельство о государственной регистрации объекта интеллектуальной собственности №286. Зарегистрировано в Комитете по правам интеллектуальной собственности Министерства юстиции Республики Казахстан. – Астана. 2008. – № 286.
  • Самигулина Г.А., Самигулина З.И. Оценка энергетических погрешностей искусственной иммунной системы по гомологам (программа для ЭВМ). Свидетельство о государственной регистрации объекта интеллектуальной собственности №396. Зарегистрировано в Комитете по правам интеллектуальной собственности Министерства юстиции Республики Казахстан. – Астана. 2008. – №396.
  • Самигулина Г.А., Самигулина З.И. Разработка интеллектуальной системы управления дистанционным образованием на основе иммунносетевого моделирования (программа для ЭВМ). Свидетельство о государственной регистрации объекта интеллектуальной собственности в Комитете по правам интеллектуальной собственности МЮ РК. – Астана, 27 декабря 2010. – №1882.- 19с.
  • Самигулина Г.А., Самигулина З.И. Разработка технологии иммунносетевого моделирования для компьютерного молекулярного дизайна лекарственных препаратов (программа для ЭВМ). Свидетельство о государственной регистрации прав на объект авторского права в Комитете по правам интеллектуальной собственности МЮ РК. –Астана, 28 марта 2011. – № 473. – 23c.
  • Самигулина Г.А., Самигулина З.И. Разработка интеллектуальной стохастической системы управления на основе иммунносетевого моделирования (программа для ЭВМ). Свидетельство о государственной регистрации прав на объект авторского права в Комитете по правам интеллектуальной собственности МЮ РК. –Астана, 4 июня 2012. – №675. – 23c.
  • Самигулина Г.А., Самигулина З.И. Интеллектуализация процесса обработки данных на основе подхода искусственных иммунных систем для систем промышленной автоматизации // Свидетельство о государственной регистрации прав на объект авторского права (программа для ЭВМ). – Астана, 4 декабря 2013г., №1601, -18с.
  • Самигулина З.И., Ширяева О.И., Самигулина Г.А. Адаптивные системы управления сложными объектами в аэрокосмической области // Свидетельство о государственной регистрации прав на объект авторского права (программа для ЭВМ). –Астана, 2014., – № 222 от 18 февраля 2014, – 29с.
  • Самигулина Г.А., Самигулина З.И., Самигулин Т.И. Программное обеспечение Data_Preprocessing для предварительной обработки данных // Свидетельство о государственной регистрации прав на объект авторского права (программа для ЭВМ). –Астана, 2016. – № 0189 от 28 января 2016. – 9 с.
  • Самигулина Г.А., Шаяхметова А.С., Сулеймен О.О. Программное обеспечение «DLS_PIV» (Distance learning system for people with impaired vision) для дистанционного обучения людей с ограниченными возможностями зрения (программа для ЭВМ) // Свидетельство о государственной регистрации прав на объект авторского права (программа для ЭВМ). –Астана, 2016. – № 0090 от 15 января 2016. – 25 с.
  • Самигулин Т.И., Ширяева О.И., Самигулина З.И., Самигулина Г.А. Програмное обеспечение GeneticPRegulator для решения задачи управления сложными объектами // Свидетельство о государственной регистрации прав на объект авторского права (программа для ЭВМ). – Астана, – №1824 от 19 августа 2016. – 19с.
  • Самигулина Г.А., Нюсупов А.Т., Шаяхметова А.С. Авт.св. № 1614 от 3 июля 2017 г. (на программу ЭВМ) «Программное обеспечение «MAS_DL_PIV» (Multi –Agent System of Distance Learning for People with ImpairedVision) – мультиагентная система для дистанционного обучения людей с ограниченными возможностями зрения
  • Самигулина Г.А., Масимканова Ж.А. Авт.св. № 3191 от 25 декабря 2017 г. (на программу ЭВМ) «Программное обеспечение «SIIM» (Swarm Intelligence for Immune network Modeling) – Роевой Интеллект для Иммуносетевого Моделирования
  • Самигулина Г.А., Самигулин Т.И. Авт.св. №836, опубл. 06.12.2018 МЮ РК. «АССО (Ant Colony for complex object) »